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Amany FaragView profile

Associate Professor

• Patient Safety
• Medication Safety
• Nurse Fatigue
• +4 more

Amany Farag is a tenured Associate Professor at the University of Iowa College of Nursing and Co-Director of the VA Quality Scholars Program (Iowa City site). Her work bridges nursing science, human factors engineering, and data science to address critical patient safety challenges, with a specific focus on medication administration practices across healthcare settings. Education: Postdoctoral Scholar, Case Western Reserve University, Frances Payne Bolton School of Nursing PhD, Case Western Reserve University, Frances Payne Bolton School of Nursing MSN, University of Alexandria, Alexandria Egypt BSN, University of Alexandria, Alexandria Egypt Dr. Farag's research centers on reactive and proactive approaches to patient safety , with dual emphasis on medication error reporting systems and nurse fatigue prevention. Her work integrates human factors engineering and machine learning to develop novel interventions. Key themes include understanding how social and system factors influence nurses' error reporting behaviors, examining fatigue as a precursor to errors, and developing self-management strategies for nurse wellness. Recent projects explore intershift recovery, sleep hygiene using consumer technology, and the impact of shift work on cognitive performance. Publication trends reveal a strong focus on interdisciplinary safety science , with consistent output in nursing, human factors, and healthcare quality journals. Her work increasingly incorporates AI methodologies while maintaining clinical relevance to frontline nursing practice. Scientific Recognition: Mary Hanna Memorial Journalism Award (Journal of Peri-Anesthesia Nursing, 2016) Author of the Year (Journal of Emergency Medicine, 2018) Junior Investigator Award (Midwest Nursing Research Society, 2018) Rogers Endowed Lectureship Award (Mississippi Medical Center, 2018) Dr. Farag secures significant funding from national agencies including the National Council of State Boards of Nursing (NCSBN), NIOSH-funded Healthier Workforce Center of the Midwest, CDC-funded Injury Prevention Research Center, and University of Iowa Institute for Clinical and Translational Science. Her collaborative approach spans nursing, data science, ergonomics, and public health teams. As Co-Director of the VA Quality Scholars Program, she mentors future healthcare quality leaders while advancing her research on medication safety systems and nurse fatigue mitigation strategies through interdisciplinary partnerships.

Ivan ViolaView profile

Associate Professor

• Visualization
• Computer Graphics
• Biological Visualization
• +3 more

Ivan Viola is an Associate Professor at the Institute of Computer Graphics and Algorithms, part of the Faculty of Informatics at TU Wien, Austria. He holds a leave of absence until December 2024 while also being affiliated with King Abdullah University of Science and Technology (KAUST) as an Associate Professor funded by the Vienna Research Groups program. His research focuses on visualization techniques in medicine, biological sciences, and earth sciences, with a specialty in illustrative visualization and DNA-nanotechnology applications. Viola has contributed over 100 scientific works and serves as a reviewer and panelist for major conferences in computer graphics and visualization. Education: M.Sc. (2002) and Ph.D. (2005) in Computer Graphics from TU Wien. Postdoctoral research at the University of Bergen (2006-2011), where he became Full Professor before returning to TU Wien. Research Interests: Whole-cell visualization Molecular modeling Interactive 3D environments Biomedical visualization Data-driven colormap techniques Awards: IEEE VIS 2017 Best Paper Honorable Mention, 'Best Overall Concept' for CellView, and multiple visualization awards. Active in EuroVis and IEEE VIS organizing roles. Grants & Supervision: Leads the Visualization Group at TU Wien, supervising student projects and master’s theses. Involved in grants like the Vienna Research Groups program. Labs/Teams: Visualization Group at TU Wien, collaborating on projects like CellView and Molecumentary.

• Rheumatology
• Liver Disease
• Alcoholic Hepatitis
• +3 more

Krishnasai Abhishek Madathanapalli is a Clinical Fellow in the Section of Rheumatology, Allergy, and Immunology at Yale School of Medicine since July 2023. He holds the rank of Research Fellow and works under mentorship of Monique Hinchcliff, MD, MS. His academic journey spans diverse environments: born in Bahrain, medical training in India (MBBS 2018), residency at University of Connecticut (2023), and prior research experience at Indiana University’s Department of Gastroenterology and Hepatology. Education: MBBS in Medicine: Jawaharlal Institute of Post-Graduate Medical Education and Research, Pondicherry, India (2018) Residency in Internal Medicine: University of Connecticut School of Medicine (2023) Visiting Research Scholar: Indiana University Department of Gastroenterology and Hepatology Research Interests: Krishnasai’s work bridges rheumatology and immunology with liver disease research. He focuses on health-related quality of life assessment in chronic conditions, biomarker dynamics (e.g., myostatin), and translational studies for alcoholic hepatitis. His research emphasizes patient-centered outcomes and improving clinical tools for liver disease evaluation. Awards: Yale International Physician-Scientist Resident and Fellow Research Award (2023) Rheumatology Research Foundation Resident Research Preceptorship Award (2022, International) Advising & Grants: Supported by grants from the Rheumatology Research Foundation and Yale School of Medicine, he collaborates with the Clinical and Translational Research Accelerator directed by Dr. Hinchcliff. No formal advisees/students are listed, but his mentorship and grant activities reflect active participation in physician-scientist development programs. Labs & Teams: Affiliated with the Section of Rheumatology, Allergy, & Immunology at Yale and engaged in interdisciplinary research through the Janeway Society and Office of Physician-Scientist Development initiatives.

• Machine Learning
• Artificial Intelligence
• Virtual Reality
• +3 more

Simon Colreavy Donnelly is an Associate Professor in the Department of Computer Science & Information Systems at the University of Limerick. He is a member of the Interaction Design Centre and focuses on interdisciplinary research at the intersection of artificial intelligence, educational technology, and healthcare informatics. His work spans machine learning applications in medical data analysis, virtual reality (VR) and extended reality (XR) for inclusive education, and deep learning techniques in chemical analysis and spectroscopy. Research Interests: His primary areas of investigation include generative AI for education equity, semisupervised learning algorithms, virtual learning environments design, and the ethical deployment of immersive technologies in healthcare and palliative care. He also explores NMR spectroscopy analysis using deep learning and develops tools for nutritional content estimation through image processing. Collaborations: His recent collaborations span international teams addressing challenges in toxicity-free online discourse (PAN 2024), semisupervised learning distribution mismatches, and VR applications for post-pandemic blended learning. His work integrates computational methods with real-world applications in education, healthcare, and chemical analysis. Labs/Teams: Active within the Interaction Design Centre at UL, his research group develops practical solutions for accessibility in digital education and healthcare systems, emphasizing user-centered design principles for extended reality applications.

Rachel HarrisonView profile

Professor

• Software Engineering
• Machine Learning
• Requirements Engineering
• +3 more

Professor Rachel Harrison is a Professor in Computer Science at the School of Engineering, Computing and Mathematics, Oxford Brookes University. Her research focuses on software metrics, machine learning, and requirements engineering with emphasis on empirical and automated software engineering solutions. She has over 160 publications and extensive industry collaborations with organizations like IBM and Philips Research Labs. Her work has been recognized through roles as Editor-in-Chief of the Software Quality Journal and leadership in conferences such as ICSE and ESEM. She leads the Dependable System Engineering Centre (DSERC) and is part of the Artificial Intelligence, Data Analysis and Systems (AIDAS) Institute and the Applied Software Engineering and Data Analytics (ASEDA) Group. Her research projects include AI applications for big data analysis (AIMi), automated review classification (ReClass), and software quality improvement (SEQUIN). Professor Harrison has served on over 50 international program committees and initiated workshops like RAISE and AIRE. Her teaching includes advanced computer science modules and leadership in courses like Essential Maths for University Study and Advanced Software Development . Her work bridges academic research and practical applications, particularly in healthcare technology (e.g., diabetes management systems) and mobile application usability. She advocates for rigorous software quality practices and has contributed to frameworks for requirements validation and risk assessment in software projects.

• Computer Science
• Data Visualization
• Scientific Visualization
• +3 more

Robert S. Laramee is a Professor at the University of Nottingham (previously at Swansea University), specializing in visualization research. His work focuses on data visualization, scientific visualization, and computational fluid dynamics. He has authored over 170 publications in top journals like IEEE Transactions on Visualization and Computer Graphics, Computer Graphics Forum, and IEEE Computer Graphics and Applications. Research Interests: His research spans information visualization, flow visualization, visual literacy, and educational aspects of visualization. He emphasizes practical applications in fields like healthcare, digital humanities, and computational science. Recent Trends: Recent work includes studies on treemap literacy, educational frameworks for visualization, and interactive systems for clinical data. He has also contributed to visualization resources and surveys, aiming to bridge academic and industry needs. Grants & Collaborations: Collaborations include projects on visualization for smart cities, protein-lipid interactions, and quantum chromodynamics data analysis. No specific grant details are provided in the text. Labs & Teams: Affiliated with visualization research groups at Nottingham and Swansea, though specific lab names are not mentioned.

• Health Communication
• Digital Health
• AI
• +7 more

Prof. Julia van Weert is a Professor of Health Communication at the Faculty of Social and Behavioural Sciences of the University of Amsterdam. Her research focuses on improving patient-provider communication through digital health interventions, shared decision-making processes, and health equity. Specializing in areas such as AI applications in healthcare, cancer care communication, and falls prevention in older adults, her work bridges communication science with practical healthcare challenges. She leads projects like the SNOWDROP initiative, which uses big data to empower seniors in managing medication-related fall risks. Her studies frequently address barriers to effective communication in multicultural healthcare settings and the impact of online health information on patient outcomes. Key collaborations include work with Amsterdam UMC and ASCoR, emphasizing user-centered design for clinical decision support systems. Her expertise spans health literacy, pandemic communication during crises, and the role of mental wellbeing in health messaging. Notable projects include systematic reviews on decision aids for older adults and longitudinal studies on media consumption patterns during the COVID-19 pandemic. Prof van Weert’s research integrates qualitative and quantitative methods, often involving cross-disciplinary teams to address complex healthcare communication challenges. She has contributed to the development of clinical tools like the ADFICE_IT system for deprescribing fall-risk drugs and the Online Value Clarification Tool for early-phase clinical trials. Her work emphasizes translating academic findings into actionable strategies for improving healthcare delivery and patient empowerment across diverse populations.

Abani PatraView profile

Professor

• Computational Sciences
• Data Driven Modeling
• Computer Science
• +5 more

Abani Patra is a Professor of Computer Science, Mathematics, Mechanical Engineering, and Civil and Environmental Engineering at Tufts University. He also serves as the Center Director for Data Science at the Tufts Institute for Artificial Intelligence (TIAI). His research focuses on computational sciences and data-driven modeling, with applications spanning environmental systems, biomedical imaging, and geophysical hazards. He has directed major initiatives at the National Science Foundation (NSF) and U.S. Department of Energy (DOE), and previously founded the Institute for Computational and Data Sciences at the University at Buffalo. Education: PhD in Mathematics, University of Texas, 1995 MS in Mechanical Engineering, University of Missouri, 1990 BSc in Engineering, Birla Institute of Technology & Science, India Research Interests: Large-scale computational modeling and uncertainty quantification Data-driven approaches for geophysical hazards (e.g., debris flows, volcanic eruptions) Biomedical imaging and metabolic analysis Open science platforms for glaciology and volcanology Key Projects: Developed the Ghub platform for open cryosphere research Launched VICTOR, a cyberinfrastructure for volcanology Advanced AI-driven techniques for postfire debris flow prediction Grants & Leadership: Directed NSF and DOE programs in computational science PI for NSF Cyberinfrastructure grants Former director of the Institute for Computational and Data Sciences

• Biomedical Informatics
• Data Science
• Machine Learning
• +7 more

Lucila Ohno-Machado, MD, PhD, MBA, is the Waldemar von Zedtwitz Professor of Medicine and Biomedical Informatics and Data Science at Yale University. She serves as Deputy Dean for Biomedical Informatics and Chair of the Department of Biomedical Informatics and Data Science at the Yale School of Medicine. Her leadership roles include overseeing informatics infrastructure for Yale’s academic health system and fostering interdisciplinary collaboration across departments such as Medicine and the Halicioğlu Data Science Institute (previously at UCSD). Ohno-Machado holds an MD from the University of São Paulo (Brazil), an MBA from Fundação Getúlio Vargas (Brazil), and a PhD in Medical Information Sciences and Computer Science from Stanford University. She has held faculty positions at Harvard Medical School, MIT’s Health Sciences and Technology Division, and the UCSD Health Department of Biomedical Informatics, where she pioneered federated learning and privacy-preserving AI methodologies. Her research focuses on predictive analytics, federated learning, quantum computing in healthcare, and blockchain applications to enhance data security. She emphasizes addressing algorithmic bias and promoting health equity through data-driven solutions. Recent work includes developing frameworks for medical device safety evaluation and guiding principles to mitigate disparities in algorithmic healthcare applications. Key achievements include the Inaugural Helen M. Ranney Award (2024), election to the National Academy of Medicine (2024), and the William W. Stead Award (2019). She has led NIH-funded informatics centers and contributed to the first large-scale clinical data-sharing initiative across five UC medical systems. Her grants span AHRQ, PCORI, NSF, and blockchain-related initiatives through the IT/NIST Challenge Award. Ohno-Machado advises on translational research strategies and mentors teams in YBIC (Yale Biomedical Informatics & Computing). Her lab collaborates globally, leveraging federated models and AI to advance personalized medicine while prioritizing patient privacy. She also chairs the OHER Awards for Yale Research Excellence, promoting interdisciplinary health equity research.

Adalberto Campos FernandesView profile

Associate Professor

• Health Administration
• Health Management
• Health Policies
• +4 more

Adalberto Campos Fernandes is an Associate Professor at the National School of Public Health (NOVA-NSPH), Universidade NOVA de Lisboa, and a researcher at the Centro de Investigação em Saúde Pública (CISP/PHRC) and Comprehensive Health Research Centre (CHRC). He holds a PhD in Health Administration from Universidade de Lisboa. Previously, he served as Minister of Health of Portugal (2015–2018) and held leadership roles in major hospitals and healthcare institutions, including the Board of Directors of Hospital de Santa Maria and Hospital Pulido Valente. Education: PhD in Health Administration (Universidade de Lisboa), Master in Public Health (ENSP-NOVA), Specialist in Public Health, and Medical Degree (Faculdade de Medicina de Lisboa). Research Focus: Health Administration, Health Management, Sustainability of Health Systems, and Public-Private Partnerships in Healthcare. His work emphasizes the integration of social and health sectors, policy analysis, and healthcare system sustainability. Recent research explores decentralized healthcare models, the impact of AI in clinical coding, and obesity management strategies. He has contributed to over 96 publications and actively participates in policy debates on healthcare accessibility and system resilience. Key roles beyond academia include serving on the Board of Directors of several hospitals and leading initiatives in public-private healthcare collaborations. His professional experience bridges academic research, policy-making, and clinical administration, shaping Portugal’s healthcare landscape.

Edward KimView profile

Associate Professor

• Computer Vision
• Sparse Coding
• Neuromorphic Computing
• +12 more

Edward Kim is an Associate Professor in the Department of Computer Science at Drexel University's College of Computing & Informatics. His research spans computer vision, sparse coding, neuromorphic computing, and AI, with a focus on neuro-inspired machine learning and robust, interpretable models. Research Interests: Computer Vision Sparse Coding and Dictionary Learning Neuromorphic and Spiking Neural Networks Explainable and Adversarially Robust AI Multimodal Learning Medical Image Processing His recent publications highlight a strong trend in developing biologically inspired, robust, and interpretable machine learning models, particularly using sparse coding and spiking neural networks. Themes include adversarial robustness, model confidence calibration, and cross-modal integration. His work often bridges neuroscience and AI, aiming to create more human-like and trustworthy systems. Scientific Awards: NSF CAREER Award (2019) Longsview Fellow (collaborative project, 2021) Dr. Kim advises several graduate students in the SPARSE Lab and has secured significant research funding from the NSF, DARPA, and the Bill & Melinda Gates Foundation. His grants focus on ethical AI, racial bias in ML, and digital health platforms. He also contributes to academic leadership as a Provost Fellow at the Drexel Solutions Institute and co-chair of computer vision tracks at major conferences. Labs and Teams: He leads the SPARSE (SPiking And Recurrent SOFTwarE) Coding Lab, which investigates biologically inspired learning models beyond traditional deep learning. The lab integrates neuroscience principles to improve stability, interpretability, and robustness in AI systems.

Michael KrauthammerView profile

Professor

• Clinical Data Science
• Translational Bioinformatics
• Machine Learning in Healthcare
• +3 more

Michael Krauthammer is a Professor of Medical Informatics and Chair of the Department of Quantitative Biomedicine at the University of Zurich, affiliated with the University Hospital of Zurich. His lab focuses on Clinical Data Science and Translational Bioinformatics, leveraging AI and machine learning to address healthcare challenges. Key areas include cancer genomics, federated learning, and automated medical imaging analysis. Education and affiliations: Krauthammer leads an interdisciplinary team supported by major funding agencies. His research spans bioinformatics, clinical decision support systems, and multimodal data integration. Notable projects include AI-assisted diagnosis in rheumatology and prime editing efficiency prediction. Recent work emphasizes longitudinal cfDNA analysis, drug interaction modeling, and personalized oncology. The lab collaborates across disciplines, with projects funded by Swiss and international grants. Students and postdocs work on topics like machine learning for radiology reports, longitudinal disease trajectories, and protein design. Key projects include the NTCIR-18 RadNLP challenge, prime editing prediction models (Nature Biotechnology 2024), and vision transformers for capillaroscopy analysis. The lab advocates for reproducible data science and ethical AI in healthcare.

• Health Policy and Systems Research
• Social Determinants of Health
• Participatory Action Research
• +9 more

Dr. Lucia D'Ambruoso is a Senior Lecturer at the Institute of Applied Health Sciences, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen. She is based at the Aberdeen Centre for Health Data Science and leads international research on health systems, participatory methods, and verbal autopsy. She holds honorary and visiting positions at the University of the Witwatersrand (South Africa), Umeå University (Sweden), and Stellenbosch University, and serves on multiple international research and policy committees. PhD in Public Health, University of Aberdeen (2011) MSc in Public Health and Health Services Research, University of Aberdeen (2003) BSc (Hons) in Pharmacology, University of Aberdeen (1997) Her research focuses on health policy and systems, social determinants of health, and participatory action research, especially in sub-Saharan Africa and South Asia. She uses qualitative and mixed methods to understand how health systems can be made more equitable and responsive through community engagement, inter-sectoral action, and innovative data systems like verbal autopsy. Her recent publications demonstrate a strong focus on community-led health research, digital health platforms for emergency care, school-based mental health, and mortality data systems. She leads major NIHR and GCRF-funded programmes in South Africa and Rwanda, aiming to strengthen primary care and injury response systems through participatory methods. Scientific Awards: University of Aberdeen Interdisciplinary Research Award (2024) University of Aberdeen Outstanding Research Award (2024) Fellow, Stellenbosch Institute of Advanced Study (2025) Fellow, Royal Society for Public Health (2021) Fellow, Higher Education Academy (2017) Dr. D'Ambruoso teaches across global health, health policy, and research methods at both undergraduate and postgraduate levels. She supervises PhD students and is Deputy Director of the Centre for Global Development at the University of Aberdeen. She is actively involved in community engagement through NHS Grampian and serves on the editorial board of Global Health Action and the Steering Committee of the Politics of Health Group. Her research is supported by NIHR, MRC, Wellcome Trust, and international philanthropies. She leads the Verbal Autopsy with Participatory Action Research (VAPAR) initiative, which connects communities, researchers, and policymakers to generate actionable evidence on health equity. Her team works closely with the Agincourt HDSS in South Africa and has developed innovative tools for community health worker training and data collection.

Sinead LanganView profile

Professor

• Clinical Epidemiology
• Immune-Mediated Inflammatory Diseases
• Atopic Eczema
• +4 more

Professor Sinead Langan is a leading clinical epidemiologist at the London School of Hygiene & Tropical Medicine (School of Epidemiology and Population Health, Department of Non-communicable Disease Epidemiology). She maintains dual roles as a clinical dermatologist at St John's Institute of Dermatology, Guy's and St Thomas' Hospital, and as academic director for Health Data Research UK London. Queen's University Belfast (MD) - 2005 University of Nottingham (PhD) - 2011 University of Pennsylvania (Visiting Scholar) - Postdoctoral Her research spans two critical domains: Immune-Mediated Inflammatory Conditions : Leading groundbreaking work on atopic eczema and psoriasis using 17 million patient records through OpenSAFELY platform, revealing novel associations between severe eczema and cardiovascular outcomes Health Data Methodology : Co-founder of the RECORD initiative (www.record-statement.org) that establishes international standards for observational health data reporting Recent publications analyze: Gene-environment interactions in eczema Development of standardized protocols for routine health data analysis Cardiovascular risks in inflammatory skin diseases Long-term developmental impacts of atopic disease Pandemic effects on healthcare delivery Key awards include: Fellow of Association of Physicians (2025) National Clinical Impact Award (2022-2027) ONS Excellence & People's Choice Awards (2022) British Society Medical Dermatology Prize (2022) She directs: Coronavirus School Infection Survey (150 schools) NHS indirect effects monitoring during pandemic

Kamal MahtaniView profile

Professor

• Evidence-Based Healthcare
• Primary Care
• Health Services Research
• +5 more

Prof Kamal R Mahtani is a Professor of Evidence-Based Healthcare at the University of Oxford , based at the Centre for Evidence-Based Medicine within the Nuffield Department of Primary Care Health Sciences. He is a practicing NHS General Practitioner and co-founder of the Oxford Social Prescribing Research Network. Adjunct Professor at University of New South Wales (2025) Fellow of Kellogg College and Royal College of General Practitioners Research Interests focus on service innovations in primary care, including social prescribing, evidence translation, and workforce dynamics (paramedics, pharmacists, link workers). His work bridges healthcare delivery with behavioral science and policy impact. Publications emphasize realist evaluations, systematic reviews, and meta-analyses across social prescribing, chronic disease management, and data-driven prescribing interventions. Notable funding includes NIHR Fellowships and £1.2M for the Oxford Social Prescribing Research Network. Awards include: 2016 RCGP/SAPC Yvonne Carter Award 2020 RCGP/SAPC John Fry Award Key role in Athena Swan Gold award (2023) via leadership development Education & Leadership features directing Oxford's MSc Global Healthcare Leadership and Primary Care Research Leadership Programme, alongside graduate medical education (BSc, PhD, MBBS, FRCGP). He advocates for diversity in academia as the first British-Indian Oxford Professor in his department.